AWS Partner Webcast - Fast Insights from Disparate Data with Amazon Redshift and ClearStory Data


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Organizations relying on data intelligence depend on fast-cycle analysis. In this webinar, you will learn how to use ClearStory and Amazon Redshift to quickly bring together more sources of internal and external data, and discover new insights.

ClearStory is an integrated application and platform, speeding analysis across internal & external data. You can access internal and external data, speed data manipulation by up to 80%, and see insights through visual data updates.

What you’ll learn:
- How Amazon Redshift & ClearStory Data bring a new approach to speed in-depth analysis across diverse data sets
- How ClearStory’s simple, collaborative user model and visualization features ease discovering insights
- Customer case studies for the joint solution across retail, consumer packaged goods and online businesses

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AWS Partner Webcast - Fast Insights from Disparate Data with Amazon Redshift and ClearStory Data

  1. 1. Get Insights from Disparate Data Quickly with Amazon Redshift and ClearStory Data
  2. 2. Webinar Overview  Submit Your Questions using the Q&A tool.  A copy of today’s presentation will be made available on:  AWS SlideShare Channel@  AWS Webinar Channel on YouTube@ nPlVzJI-ccQXlxjSvJmw
  3. 3. Introducing Tina Adams Product Manager Amazon Web Services Vaibhav Nivargi Technical Co-founder ClearStory Data
  4. 4.  Overview of Amazon Redshift data warehouse  How ClearStory’s simple and collaborative user model eases discovering insights in Amazon Redshift  Demo  Q&A What We’ll Cover
  5. 5. Fast, simple, petabyte-scale data warehousing for less than $1,000/TB/Year Amazon Redshift
  6. 6. Amazon Redshift Architecture • Leader Node – SQL endpoint – Stores metadata – Coordinates query execution • Compute Nodes – Local, columnar storage – Execute queries in parallel – Load, backup, restore via Amazon S3; load from Amazon DynamoDB or SSH • Two hardware platforms – Optimized for data processing – DW1: HDD; scale from 2TB to 1.6PB – DW2: SSD; scale from 160GB to 256TB 10 GigE (HPC) Ingestion Backup Restore JDBC/ODBC
  7. 7. Amazon Redshift is priced to let you analyze all your data • Number of nodes x cost per hr • No charge for leader node • No upfront costs • Pay as you go DW1 (HDD) Price Per Hour for DW1.XL Single Node Effective Annual Price per TB On-Demand $ 0.850 $ 3,723 1 Year Reservation $ 0.500 $ 2,190 3 Year Reservation $ 0.228 $ 999 DW2 (SSD) Price Per Hour for DW2.L Single Node Effective Annual Price per TB On-Demand $ 0.250 $ 13,688 1 Year Reservation $ 0.161 $ 8,794 3 Year Reservation $ 0.100 $ 5,498
  8. 8. Amazon Redshift Feature Delivery Service Launch (2/14) PDX (4/2) Temp Credentials (4/11) Unload Encrypted Files DUB (4/25) NRT (6/5) JDBC Fetch Size (6/27) Unload logs (7/5) 4 byte UTF-8 (7/18) Statement Timeout (7/22) SHA1 Builtin (7/15) Timezone, Epoch, Autoformat (7/25) WLM Timeout/Wildcards (8/1) CRC32 Builtin, CSV, Restore Progress (8/9) UTF-8 Substitution (8/29) JSON, Regex, Cursors (9/10) Split_part, Audit tables (10/3) SIN/SYD (10/8) HSM Support (11/11) Kinesis EMR/HDFS/SSH copy, Distributed Tables, Audit Logging/CloudTrail, Concurrency, Resize Perf., Approximate Count Distinct, SNS Alerts (11/13) SOC1/2/3 (5/8) Sharing snapshots (7/18) Resource Level IAM (8/9) PCI (8/22) Distributed Tables, Single Node Cursor Support, Maximum Connections to 500 (12/13) EIP Support for VPC Clusters (12/28) New query monitoring system tables and diststyle all (1/13) Redshift on DW2 (SSD) Nodes (1/23) Compression for COPY from SSH, Fetch size support for single node clusters, new system tables with commit stats, row_number(), strotol() and query termination (2/13) Resize progress indicator & Cluster Version (3/21) Regex_Substr, COPY from JSON (3/25)
  9. 9. Amazon Redshift integrates with multiple data sources Amazon S3 Amazon EMR Amazon Redshift DynamoDB Amazon RDS Corporate Datacenter
  10. 10. ClearStory Data Solution June 3rd.. 2014
  11. 11. ClearStory Solution Faster, Interactive Insights for LOB Users & Data Analysts Fast, blended insights combining private data sources and external sources with a new interactive and collaborative user model Distributed Teams Business Users Data Analysts Data Stewards
  12. 12. Why Companies Choose ClearStory 1. Fast-cycle analysis accessing & converging data from multiple sources. How? Data inference eliminates traditional data modeling steps + automated Data Harmonization/blending 2. On-going diagnostic and exploratory analysis How? Uncover insights faster as data updates at source 3. Interactive and collaborative user model to speed observations & decisions. How? A new user model with collaboration, for any skillset
  13. 13. Data Sources - RedShift, RDBMS, EDW - Big Data platforms - External Premium/Public data ClearStory Integrated Application & Processing Platform Data Inference & Profiling Harmonization Visualization Collaboration Data Convergence ClearStory Platform ClearStory Application
  14. 14. Healthcare Provider • Determine patterns on doctor diagnosis and clinical trials • Reconcile and harmonize all data streams by zip code Major Retailer – Close Rate Analysis by Location • Identify factors affecting product sales - by location/zipcode and time of day Customer Examples CPG – Daily analysis on dairy product sales by location • Diverse data sources converged in Redshift, updating daily • ClearStory for harmonized holistic, intra-day analysis “Answers that used to take 60 to 90 days to pull together can now be seen in a day. The speed of execution is dramatically different than what it was before.” CPG Leader in Dairy
  15. 15. What You Will See Today 1. Speed to Interactive Insights Accessing Redshift + automated data inference + data harmonization/blending 2. Fast Interactive, Collaborative insights 3. Analysis self-updates as data updates (Data Stories updating intra-day, daily, weekly…) For Data Stewards and LOB Users
  16. 16. ClearStory & Redshift Demo Request a Trial
  17. 17. Contacts and Q&A Contacts: ClearStory Data: email: AWS Contact: